Planning an implantation of a cardiac implant

ABSTRACT

The present invention relates to a medical imaging system ( 10 ) for planning an implantation of a cardiac implant ( 42 ), comprising: a receiving unit ( 12 ) for receiving a plurality of three-dimensional (3D) cardiac images ( 14, 14 ′) showing different conditions of a heart ( 32 ) during a cardiac cycle; a segmentation unit ( 22 ) for segmenting within the plurality of 3D cardiac images ( 14, 14 ′) a target implant region ( 38 ) and a locally adjacent region ( 40 ) that could interfere with the cardiac implant ( 42 ); a simulation unit ( 24 ) for simulating the implantation of the cardiac implant ( 42 ) within the target implant region ( 40 ) in at least two of the plurality of 3D cardiac images ( 14, 14 ′); a collision evaluation unit ( 26 ) for evaluating an overlap ( 46 ) of the simulated cardiac implant ( 42 ) with the segmented locally adjacent region ( 40 ) in at least two of the plurality of 3D cardiac images ( 14, 14 ′); and a feedback unit ( 28 ) for providing feedback information to a user concerning the evaluated overlap ( 46 ).

This application is the U.S. National Phase application under 35 U.S.C.§ 371 of International Application No. PCT/EP2014/061254, filed on May30, 2014, which claims the benefit of EP Application No. 13170984.2filed on Jun. 7, 2013. These applications are hereby incorporated byreference herein.

FIELD OF THE INVENTION

The present invention relates to a medical imaging system for planningan implantation of a cardiac implant. Furthermore, the present inventionrelates to a corresponding method for planning an implantation of acardiac implant. It also relates to a computer program comprisingprogram code means for causing a computer to carry out the steps of saidmethod. An exemplary technical application of the present invention isthe planning of a transcatheter aortic valve implantation (TAVI) fortreating aortic stenosis.

BACKGROUND OF THE INVENTION

Valvular heart diseases are among the most prominent causes of heartfailure and premature cardiac death. Aortic valve stenosis is a verycommon valvular disease. This disease is often treated by implanting anartificial aortic valve via an open cardiac surgery. This is, however, avery invasive and expensive treatment. In addition, it is considered toohigh risks or contraindicated for many patients.

In the last decade, techniques for minimally invasive aortic valveimplantation have been developed that offer a new treatment option. Analternative method for high-risk patients that cannot undergo anopen-heart surgery for aortic valve replacement is a transcatheteraortic valve implantation (TAVI). In this technique, an artificial valveis mounted on a stent which is delivered through a catheter, eithertransfemoral, transsubclavian, or trans-apical, under X-ray guidance,and then expanded in-place.

Although TAVI is less invasive, its long-term outcome is unclear. Acurrent discussion is therefore, if TAVI is also beneficial for patientswith only intermediate risk for valve replacement. Because theirexpected lifetime is much longer, the long-term benefit of the TAVIimplant must be ensured.

If the TAVI implant is placed too low, i.e. reaching too far into theleft ventricular outflow tract, it can impair movement of the anteriormitral leaflet. Case reports demonstrated that contact between theimplant and the mitral valve leaflet led to mitral endocarditis andleaflet aneurysms, see e.g. Piazza, N. et al.: “Two cases of aneurysm ofthe anterior mitral valve leaflet associated with transcatheter aorticvalve endocarditis: a mere coincidence?”, in Journal of Thoracic andCardiovascular Surgery 140(3) (2010) e36-e38.

First, repetitive friction between the implant and the leaflet coulddamage the leaflet surface. Second, the implant could act as anendocarditis bridge that favors the spread of aortic valve endocarditisto the mitral valve. Especially, the slow tissue degeneration caused byrepetitive friction might become more relevant the longer the implant ispresent.

Therefore, preparing and planning medical procedures like TAVI beforebeginning an actual operation is of utmost importance. The treatmentplanning should particularly make sure to avoid the above explainedfriction between the implant and any anatomical structure of the heart.Such medical imaging procedures are also important to guide theimplantation during the surgery (in real-time), since the aortic valveanatomy is not clearly visible when using X-ray imaging.

Wächter et al.: “Patient specific models for planning and guidance ofminimally invasive aortic valve implantation”, MICCAI 2010, part I, LNCS6361, pp. 526-533, 2010, Springer-Verlag Berlin Heidelberg 2010, presenta method to extract the aortic valve anatomy from CT images. The thereinpresented method allows for detection of anatomical landmarks byexploiting the model-based segmentation. This allows to receive a fairlyaccurate model, in particular of the aortic valve and the coronaryostia. The method is also described in WO 2011/132131 A1, a prior patentapplication filed by the applicant.

Capelli, C. et al.: “Finite Element Strategies to Satisfy Clinical andEngineering Requirements in the Field of Percutaneous Valves”, in Annalsof Biomedical Engineering, vol. 40, No. 12, December 2012, pp. 2663-2673discloses a study showing that beam elements are a convenient choicetoward a practical and reliable clinical application of finite elementmodelling of percutaneous devices for valve implantation. Similaraspects are disclosed in Capelli, C. et al.: “Patient-specificsimulations of transcatheter aortic valve stent implantation”, inMedical & Biological Engineering & Computing, Springer, Berlin, vol. 50,no. 2, pp. 183-192.

US 2011/153286 A1 discloses a method and system for virtual percutaneousvalve implantation. A patient-specific anatomical model of a heart valveis estimated based on 3D cardiac medical image data and an implant modelrepresenting a valve implant is virtually deployed into thepatient-specific anatomical model of the heart valve. A library ofimplant models, each modeling geometrical properties of a correspondingvalve implant, is maintained. The implant models maintained in thelibrary are virtually deployed into the patient specific anatomicalmodel of the heart valve to select an implant type and size anddeployment location and orientation for percutaneous valve implantation.

However, there is still need for further improvement of such medicalplanning systems.

SUMMARY OF THE INVENTION

It is an object of the present invention to provide an improved medicalimaging system of the kind mentioned above for planning an implantationof a cardiac implant. It is furthermore an object of the presentinvention to provide a corresponding method and a computer program forimplementing such method.

In a first aspect of the present invention, a medical imaging system forplanning an implantation of a cardiac implant is presented thatcomprises:

-   -   a receiving unit for receiving a plurality of three-dimensional        (3D) cardiac images showing different conditions of a heart        during a cardiac cycle;    -   a segmentation unit for segmenting within the plurality of 3D        cardiac images a target implant region and a locally adjacent        region that could interfere with the cardiac implant, wherein        the target implant region is a part of a left ventricular        outflow tract and the locally adjacent region is a part of a        mitral valve;    -   a simulation unit for simulating the implantation of the cardiac        implant within the target implant region in at least two of the        plurality of 3D cardiac images;    -   a collision evaluation unit for evaluating an overlap of the        simulated cardiac implant with the segmented locally adjacent        region in at least two of the plurality of 3D cardiac images;        and    -   a feedback unit for providing feedback information to a user        concerning the evaluated overlap.

In a second aspect of the present invention, a medical imaging systemfor planning an implantation of a cardiac implant is presented thatcomprises:

-   -   a receiving unit for receiving a plurality of three-dimensional        (3D) cardiac images showing different conditions of a heart        during a cardiac cycle;    -   a segmentation unit for segmenting within the plurality of 3D        cardiac images a target implant region and a locally adjacent        region that could interfere with the cardiac implant, wherein        the target implant region is a part of a right ventricular        outflow tract and the locally adjacent region is a part of a        tricuspid valve;    -   a simulation unit for simulating the implantation of the cardiac        implant within the target implant region in at least two of the        plurality of 3D cardiac images;    -   a collision evaluation unit for evaluating an overlap of the        simulated cardiac implant with the segmented locally adjacent        region in at least two of the plurality of 3D cardiac images;        and    -   a feedback unit for providing feedback information to a user        concerning the evaluated overlap.

In a third aspect of the present invention, a method for planning animplantation of a cardiac implant is presented, which comprises thesteps of

-   -   receiving a plurality of three-dimensional (3D) cardiac images        showing different conditions of a heart during a cardiac cycle;    -   segmenting within the plurality of 3D cardiac images a target        implant region and a locally adjacent region that could        interfere with the cardiac implant, wherein the target implant        region is a part of a left ventricular outflow tract and the        locally adjacent region is a part of a mitral valve;    -   simulating the implantation of the cardiac implant within the        target implant region in at least two of the plurality of 3D        cardiac images;    -   evaluating an overlap of the simulated cardiac implant with the        segmented locally adjacent region in at least two of the        plurality of 3D cardiac images; and    -   providing feedback information to a user concerning the        evaluated overlap.

In a fourth aspect of the present invention, a method for planning animplantation of a cardiac implant is presented, which comprises thesteps of

-   -   receiving a plurality of three-dimensional (3D) cardiac images        showing different conditions of a heart during a cardiac cycle;    -   segmenting within the plurality of 3D cardiac images a target        implant region and a locally adjacent region that could        interfere with the cardiac implant, wherein the target implant        region is a part of a right ventricular outflow tract and the        locally adjacent region is a part of a tricuspid valve;    -   simulating the implantation of the cardiac implant within the        target implant region in at least two of the plurality of 3D        cardiac images;    -   evaluating an overlap of the simulated cardiac implant with the        segmented locally adjacent region in at least two of the        plurality of 3D cardiac images; and    -   providing feedback information to a user concerning the        evaluated overlap.

In a still further aspect of the present invention, a computer programis presented comprising program code means for causing a computer tocarry out the steps of either of the above-mentioned methods when saidcomputer program is carried out on the computer.

The idea of the invention is to automatically simulate and evaluate theposition of the cardiac implant within a plurality of 3D cardiac imagesbased on a segmentation of said images. Said cardiac images may be 3D CTor MRI images. In a preferred embodiment, 3D transesophageal echography(TEE) images acquired with an ultrasound imaging system may be used.

In contrast to most of the prior art planning systems of this kind, notonly one cardiac image but a plurality of such 3D cardiac images areused for the simulation and evaluation. The term “a plurality” shall beunderstood in the context of the present invention as “at least two”.This has a couple of advantages: First, it is tedious to check a seriesof images for identifying the most relevant image for planning theimplantation of the cardiac implant. A doctor or a medical assistantusually has to manually find a suitable image which may be quitetime-consuming. Secondly, by evaluating a plurality of 3D cardiac imagesshowing different conditions of the heart during the cardiac cycle,possible unwanted collisions between the cardiac implant and parts ofthe heart that move during the cardiac cycle may be estimated in a muchmore precise manner. Depending on the heart movement, the cardiacimplant may interfere with one heart region in a first image, but maynot interfere with said region of the heart when considering it inanother image. Using a plurality of 3D cardiac images for the planningprocedure therefore allows to more precisely determining the implantposition, the size and shape of the cardiac implant.

Preferably, the plurality of 3D cardiac images is a sequence of timelyconsecutive cardiac images showing one or more complete cardiac cycles.By segmenting all of these images, a dynamic segmentation is establishedwhich allows to simulate the movement of the heart. This may either bedone in a pre-planning step before the actual implantation by means ofcardiac images that have been pre-acquired. It may, however, also bedone in real-time during the actual implantation.

A further characteristic of the presented system and method is that notonly the target implant region is segmented but also a locally adjacentregion of the heart that could, e.g. due to the heart movement,interfere with the cardiac implant. When using the presented system e.g.for TAVI, the target implant region is defined as the left ventricularoutflow tract. Depending on the size and position of the TAVI implant itcould however also interfere and overlap with the mitral valve leaflet.This mitral valve leaflet would then be considered as locally adjacentregion in the meaning of the present invention, such that it will besegmented as well. Since a plurality of 3D cardiac images are used, thisallows to evaluate possible overlaps of the TAVI implant with the mitralvalve leaflet for different positions of the leaflet during the cardiaccycle. Of course, one would say that the overlap is maximum when themitral valve is completely open. However, manually finding the imagethat exactly illustrates the open mitral valve is fairly difficult.Apart from that, collisions of the mitral valve with the cardiac implantmay also occur in other states of the mitral valve than the fully openstate.

A further characteristic of the present invention is the simulation ofthe cardiac implant within the target implant region. Preferably, asimple geometrical model may be used to simulate the cardiac implant.This simulated cardiac implant may be used to evaluate an overlap withthe locally adjacent region that has been segmented prior thereto. Afeedback unit, which may e.g. be realized by a display, then providesfeedback information concerning the evaluated overlap to a physician ormedical staff. The overlap may e.g. be displayed for all evaluatedcardiac images. This direct feedback concerning possible collisions ofthe cardiac implant with parts of the heart based on a plurality of 3Dcardiac images is a very powerful tool during planning of such a cardiacimplantation.

According to a preferred embodiment, the simulation unit is configuredto simulate the implantation of the cardiac implant within the targetimplant region in each of the plurality of 3D cardiac images, and thecollision evaluation unit is configured to evaluate the overlap of thesimulated cardiac implant with the segmented locally adjacent region ineach of the plurality of 3D cardiac images.

This means that the overlap evaluation is not only performed in a subsetof the received plurality of 3D cardiac images, but in all of thereceived 3D cardiac images. In this way, the amount of overlap data isfurther increased, such that the overlap evaluation is refined. Theoverlap data may therefore be evaluated for a whole timely consecutiveimaging sequence, meaning that the overlap of the locally adjacentregion (e.g. the mitral valve leaflet) with the virtual cardiac implantmay be calculated time-dependent over a complete cardiac cycle.

Accordingly, the feedback unit is in this embodiment configured toprovide feedback information to the user concerning the evaluatedoverlap in each of the plurality of 3D cardiac images. This feedbackinformation may be displayed for each of the 3D cardiac imagesseparately, but also in an overview for all 3D cardiac images together.

According to a further embodiment, the feedback information provided bythe feedback unit includes a quantified extent of the overlap and/or alocation where the overlap occurs in the 3D cardiac images. On adisplay, it may be exactly shown to the physician at which positions anoverlap between the simulated cardiac implant and the segmented locallyadjacent region occurs. Furthermore, an indicator about the extent ofthe overlap may be visualized. It may for example be illustrated on thedisplay that at a given position the overlap has a given size, e.g. afew millimeters.

According to a further preferred embodiment, the collision evaluationunit is further configured to determine in each of the plurality of 3Dcardiac images the overlap at a plurality of different spatial locationsalong a longitudinal axis along which the target implant regionsubstantially extends. Referring back to the example of using the systemfor TAVI, this means that the overlap between the virtual implant andthe mitral valve leaflet is calculated as a function of the implantdepth. The target implant region may then be defined as prolongation ofthe substantially elliptical left ventricular outflow tractcross-section towards the left ventricle. A coordinate system may beused as an auxiliary means, wherein the longitudinal axis of the leftventricular outflow tract indicates the z-axis. In the above-mentionedembodiment, the collision evaluation unit may determine in each of theplurality of 3D cardiac images the overlap along the z-axis, or in otherwords, as a function of the z-position.

In a preferred embodiment, the collision evaluation unit is furtherconfigured to determine for each of the plurality of different spatiallocations a maximum overlap by comparing the overlaps in the 3D cardiacimages at the respective spatial locations with each other.

In other words, the overlaps evaluated in each of the images may becompared with each other, depending on the position on the z-axis. Foreach position on the z-axis, one of the plurality of 3D cardiac imagesis selected in which the most prominent or largest overlap is detected.The result may be a motion analysis of the examined region of the heartthat, for example, shows for every or a plurality of positions withinthe left ventricular outflow tract a maximum overlap of the virtuallysimulated cardiac implant with the mitral valve leaflet over the wholecardiac cycle.

In a further preferred embodiment, the feedback unit is configured toprovide a graphical representation illustrating the maximum overlaps asa function of the different spatial locations along the longitudinalaxis z.

This graphical representation may be e.g. a graph that shows the maximumoverlap on the axis of ordinates in dependency of the position on thelongitudinal axis shown along the axis of abscissae. Since the maximumoverlap at each position on the longitudinal axis of the target implantregion has been found by comparing the overlaps at the respectiveposition in each of the 3D cardiac images, such a graph shows anaggregated overlap information taken from all received 3D cardiacimages. The term “maximum overlap” therefore indicates a relativemaximum at the respective spatial position, i.e. the highest receivedoverlap value at this spatial position when comparing the received 3Dcardiac images with each other at said position.

Referring back to the TAVI example, it has been shown that theselocation-dependent maximum overlaps between the anterior mitral leafletmovement and the prolongation of the left ventricular outflow tract varyconsiderably between different patients. Such an aggregated maximumoverlap evaluation could therefore be a good indicator for risk offriction between the mitral valve leaflet and the TAVI implant. It hasalso been shown that for some patients the absolute maximum overlap(maximum overlap value of all found relative maxima) occurs closer tothe aortic valve than for others. The above-mentioned graphicalrepresentation may therefore help a physician to identifypatient-individual risk zones.

In a further embodiment of the present invention, the segmentation unitis configured to simulate the cardiac implant by means of a virtualmodel having an elliptical cross-section, wherein a normal to theelliptical cross-section coincides with a longitudinal axis along whichthe target implant region substantially extends.

In case of the above-mentioned TAVI example, an elliptical cross-sectionis a good approximation for a cross-section of a stent that is to beimplanted into the left ventricular outflow tract. The shape or theouter contours of the virtual cardiac implant may therefore be simulatedas the prolongation of the elliptical left ventricular outflow tractcross-section towards the left ventricle. The overlap of the mitralvalve leaflet may then be calculated by mathematically determining theintersections between the segmented trajectories of the mitral valveleaflet and the elliptical tube model. In order to determine allpositions where the mitral valve leaflet extends into the leftventricular outflow tract and its linear prolongation towards the leftventricle, the virtual cardiac implant model may have an infinitelength.

According to a further embodiment, the system may additionally comprisean input interface that allows a user to vary a size, a shape and/or aposition of the simulated cardiac implant.

The overlaps may then be evaluated for different sizes, shapes andpositions of the virtual implant to automatically find the best type ofimplant and the best target implant position. Instead of usingsimplified models of the implants as mentioned above, also moresophisticated models may be used that resemble the shape and size of theimplant in a more realistic way.

According to a further preferred embodiment, the segmentation unit isconfigured to segment the target implant region and the locally adjacentregion based on a model-based segmentation.

The model-based segmentation may, for example, be conducted in a similarmanner as this is described for a model-based segmentation of CT imagesin Ecabert, O. et al. “Automatic model-based segmentation of the heartin CT images”, IEEE Transactions on Medical Imaging, Vol. 27(9), pp.1189-1291, 2008, which is herein incorporated by reference. Thismodel-based segmentation makes use of a geometrical mesh model of theanatomical structures of the heart and may comprise respective segmentsrepresenting respective anatomic features of the heart. Such amodel-based segmentation usually starts with the identification of theposition and orientation of the heart within the 3D image data. Thismay, for example, be done using a 3D implementation of the GeneralizedHough Transform. Pose misalignment may be corrected by matching thegeometrical mesh model to the image, making use of a global similaritytransformation. The segmentation comprises an initial model that roughlyrepresents the shape of the anatomical features of the heart. Said modelmay be a multi-compartment mesh model with triangular meshes. Thisinitial model will be deformed by a transformation. This transformationis decomposed in two transformations of different kinds: a globaltransformation that can translate, rotate or rescale the initial shapeof the geometrical model, if needed, and a local deformation that willactually deform the geometrical model so that it matches more preciselyto the anatomical object of interest. This is usually done by definingthe normal vectors of the surface of the geometrical model to match theimage gradient; that is to say, the segmentation will look in thereceived 3D imaging data for bright-to-dark edges (or dark-to-bright),which usually represent the tissue borders in the images, i.e. theboundaries of the anatomical features of the heart. Further details howthis model-based segmentation may be adapted to the purposes of theherein used dynamic segmentation of moving images (e.g. 4D TEE images)will be explained further below with reference to the drawings.

In the foregoing description it was mainly referred to the differentembodiments of the claimed medical imaging system. It shall beunderstood that the claimed method has similar and/or identicalpreferred embodiments as the claimed medical imaging system and asdefined in the dependent claims.

BRIEF DESCRIPTION OF THE DRAWINGS

These and other aspects of the invention will be apparent from andelucidated with reference to the embodiment(s) described hereinafter. Inthe following drawings

FIG. 1 shows a schematic block diagram of an embodiment of the medicalimaging system according to the present invention;

FIG. 2 shows a simplified flow diagram to illustrate an embodiment ofthe method according to the present invention;

FIG. 3 shows an exemplary cardiac image that has been segmentedaccording to the method of the present invention;

FIG. 4 schematically illustrates the results of the segmentation andcollision detection according to the present invention;

FIG. 5 shows a further model of the heart that may result from thesegmentation performed by the presented system;

FIG. 6 shows the model of FIG. 5 from another side;

FIG. 7 illustrates different graphs that result from an overlapevaluation according to the present invention; and

FIG. 8 shows further exemplary segmentations of cardiac images takenfrom two different patients.

DETAILED DESCRIPTION OF THE INVENTION

FIG. 1 shows a simplified and schematic block diagram to illustrate theprincipal components of the presented medical imaging system, which maybe particularly used for planning an implantation of a cardiac implant.The medical imaging system is therein in its entirety denoted withreference numeral 10.

It comprises a receiving unit (RU) 12 which is configured to receive aplurality of 3D cardiac images 14. Said plurality of 3D cardiac images14 is preferably a sequence of timely consecutive frames that areacquired with a medical imaging device (MID) 16. This medical imagingdevice 16 may be a volumetric CT scanner, an MRI scanner or a 3Dultrasound system. A particular example of a 3D ultrasound system whichmay be applied for the system of the current invention is the iE33ultrasound system sold by the applicant, in particular together with anX7-2 t TEE transducer of the applicant or another 3D transducer usingthe xMatrix technology of the applicant. Even though the presentinvention is not limited to ultrasound imaging, the following exemplaryembodiments will be described with reference to the preferably used 4DTEE ultrasound imaging technique (i.e. time-dependent 3D TEE images).

It is to be noted that the medical imaging device 16 does notnecessarily need to be a part of the medical imaging system 10 accordingto the present invention. Instead of having the 3D cardiac images 14directly (in real time) provided by a medical imaging device 16,inspected and analyzed 3D cardiac images 14′ may also be provided by astorage unit (SU) 18. The storage unit 18 may, for example, be anexternal or internal storage device like a hard drive on which 3Dcardiac images 14′ are stored which have been acquired in advance by amedical imaging device 16 or any other imaging modality.

The receiving unit 12 may be an interface (either internal or externalinterface) that receives the 3D cardiac images 14, 14′ and transfersthem to a processing unit 20. This processing unit 20 may be implementedas a CPU or a microprocessor within the medical imaging system 10. Itmay, for example, be a part of a personal computer that has softwarestored thereon that is programmed to carry out the below explainedmethod according to the present invention.

The processing unit 20 preferably comprises a segmentation unit (SEG)22, a simulation unit (SIM) 24 and a collision evaluation unit (COL) 26.The segmentation unit 22, the simulation unit 24 and the collisionevaluation unit 26 may all either be realized as separate elements orintegrated in one common processing element. All of these units 22, 24,26 may either be hardware or software implemented.

The segmentation unit 22 is configured to segment the plurality of the3D cardiac images 14, 14′. In case of a 4D TEE sequence, each frame issegmented. The simulation unit 24 is configured to simulate a model of acardiac implant as well as to simulate the implantation of the cardiacimplant in the 3D cardiac images 14, 14′. The collision evaluation unit26 then evaluates an overlap of the simulated cardiac implant withanatomical features that have been segmented in the 3D cardiac images14, 14′. The results of this evaluation may be finally shown to a user(e.g. a physician) by means of a feedback unit (FU) 28 that could berealized as a display or a screen.

Preferably, the medical imaging system 10 further comprises an inputinterface 30 that allows a user to steer the device 10 as well as tochange the parameters that are used within the image evaluationperformed by any of the units 22, 24, 26. The input interface 30 maycomprise keys or a keyboard and further inputting devices, for example atrackball or a mouse. The input interface 30 is preferably connectedeither hardwired or wireless to the processing unit 20.

FIG. 2 shows a simplified flow diagram of the method according to thepresent invention that is performed by the medical imaging system 10. Inthe following, the details of this method shall be described by means ofan exemplary transcatheter aortic valve implementation (TAVI) planningprocedure, wherein reference is additionally made to FIGS. 3 to 8.

1. First Method Step S10 (“Receive Images”)

In the first method step, a plurality of 3D cardiac images 14, 14′ arereceived by the system 10, wherein these cardiac images 14, 14′ showdifferent conditions of a heart 32, preferably of a human heart 32,during a cardiac cycle. In a preferred embodiment, these cardiac images14, 14′ include a sequence of 3D TEE images over time (also denoted as a4D TEE image sequence). This 4D TEE sequence preferably shows the heartmovement during a complete cardiac cycle. The image sequence may alsoillustrate only parts of a cardiac cycle or more than one cardiac cycle.This 4D TEE image sequence may be used to analyze the heart movement, inparticular to analyze the mitral valve motion for TAVI planning.

2. Second Method Step S12 (“Segmentation”)

In the next step, each frame of the received 4D TEE image sequence issegmented. This is preferably made by a model-based segmentation of thevalve apparatus of the heart 32 which is performed by the segmentationunit 22.

During this step, the anatomical features of interest are segmented inorder to being able to simulate the movement of these anatomicalfeatures over time. Anatomical features that are of particular interestin a TAVI are the aortic valve, the left ventricular outflow tract, intowhich the cardiac implant is inserted, as well as the anterior mitralleaflet, since, depending on the position and size of the cardiacimplant, the anterior mitral leaflet may collide with the medicalimplant during its natural movement.

FIG. 3 shows a TEE ultrasound image from which it can be seen that theanterior mitral leaflet 34 in its open position at least partly extendsinto the left ventricular outflow tract 36 where the medical implant maybe placed. In terms of the present invention, the left ventricularoutflow tract 36 is therefore denoted as target implant region 38, andthe anterior mitral valve leaflet 34 is denoted as locally adjacentregion 40 that could interfere with the cardiac implant 42, as this isschematically illustrated in FIG. 4.

In the segmentation step, at least the target implant region 38 and thelocally adjacent region 40 are segmented in a multi-step approach inorder to determine the dynamics of the left ventricular outflow tract 36and the anterior mitral leaflet 34. The model that is used thereto isrepresented as a triangular surface model with mean shape m. First, theheart position is located using an adapted Generalized Hough Transform.Next, it is iteratively refined by determining the parameters of anaffine transformation T that minimize the distance to detectedboundaries (external energy E_(ext)). Finally, multiple iterations of adeformable adaptation are performed that is balanced between attractionto image boundaries (E_(ext)) and mean shape preservation (E_(int)).Details of such a boundary detection technique may be found in thescientific paper of Ecabert, O. et al. mentioned above, as well as inPeters, J. et al.: “Optimizing boundary detection via simulated searchwith applications to multi-modal heart segmentation”, Medical ImageAnalysis 14(1) (2010) 70, which is herein incorporated by reference aswell.

For the illustrated example of TAVI planning, it is sufficient to use atriangular surface model of the left heart that comprises endocardialsurfaces of the left ventricle, the left atrium, the ascending aorta,and of the aortic and mitral valve.

The mean shape m contains two valves in half-open state. It is extendedby two linear modes φ_(m) to model the valve dynamics, similar to PCAmodes:m(p ₁ ,p ₂)= m+p ₁φ₁ +p ₂φ₂

However, these modes need not be calculated from PCA, but can becalculated as a linear interpolation between the open and closed statefor each heart valve.

The coefficients p_(m) describe the current state of each heart valve.For all vertices outside the respective valves, the vector elements ofφ_(m) are zero and do thus not influence the shape of the remainingmodel.

The adaptation process is performed as follows: After the GeneralizedHough Transform, the mean model with half-open valves is used toestimate a global rigid transformation T. At this step, no valvedynamics need to be estimated. Then, the coefficients p_(m) areoptimized during the deformable adaptation. The formulation of the shapeconstraining energy E_(int) is given as:

$E_{int} = {\sum\limits_{i = 1}^{V}\;{\sum\limits_{j \in {N{(i)}}}\;\left( {\left( {v_{i} - v_{j}} \right) - \left( {{T\left\lbrack {m_{i}\left( {p_{1},p_{2}} \right)} \right\rbrack} - {T\left( {m_{j}\left( {p_{1},p_{2}} \right)} \right\rbrack}} \right)} \right)^{2}}}$

Here, V is the number of vertices in the model, N(i) are the neighboursof the ith vertex, v_(i/j) are the vertex positions in the deformedmesh, and m_(i/j) are the vertex positions in the model.

Furthermore, a penalty term can be added to the total energy with weightβ to avoid unphysiological mode coefficients p_(m).

To analyze data from a specific patient, all cardiac phases of thereceived image data set are segmented using the model and frameworkdescribed above. To this end, the first cardiac phase is segmented, andthe result is used as initialization for the next cardiac phase. Onlythe deformable adaptation is then performed for the succeeding cardiacphases with the respective previous results as initialization.

To compensate for global movement or other displacements, all meshessegmented from one time series are then preferably registered to themesh at a endsystolic state. Most preferably, the aortic valve annuluspoints that are detected in each frame are registered onto each other tomake all heart movement relative to the target implant region 38.

As a result of the above-mentioned segmentation, the movement trajectoryof the region 40 (e.g. the anterior mitral leaflet 34) that is locallyadjacent to the target implant region 38 (e.g. the left ventricularoutflow tract 36) is determined for a plurality of different surfacepoints. This allows to animate the movement of the anterior mitralleaflet 34 in a fairly accurate manner.

In order to simplify the movement analysis of the received trajectories,a coordinate system is preferably introduced by the segmentation unit22. In the particular example of TAVI planning, this coordinate systemis preferably arranged within the target implant region 38 (the leftventricular outflow tract 36), wherein the z-axis is arranged along thelongitudinal axis along which the target implant region 38 substantiallyextends (see FIG. 5). The cross-section of the target implant region 38may then be modelled as an elliptical ring 44, wherein the x-axis isaligned along the major axis of this ellipse 44 and the y-axis along theminor axis of the ellipse (see FIG. 6). The origin of this coordinatesystem may then be shifted along the z-axis to the aortic annulus plane46. This way, all z-distances are referenced with respect to the aorticannulus plane 46.

3. Third Method Step S14 (“Implant Simulation”)

In the implant simulation step that is performed by the simulation unit24, the cardiac implant 42 and its position within the target implantregion 38 is simulated. This is preferably done in each frame of thereceived 3D image sequence. The cardiac implant 42 may thereto besimulated by means of a virtual model having an ellipticalcross-section, e.g. the cross-section of the target implant region 38that has been determined within the segmentation unit 22. In the givenexample, the elliptical ring 44 determined within the segmentation stepS12 may be extended along the z-axis along which the target implantregion 38 substantially extends. Alternatively, other virtual 3D modelsof cardiac implants 42, which resemble the shape of a stent in a morerealistic manner, may be used in the simulation. By means of the inputinterface 30, the user may also manually vary the size, the shape and/orthe position of the simulated cardiac implant 42.

4. Fourth Method Step S16 (“Collision Detection”)

In the collision detection step which is performed by the collisionevaluation unit 26, an overlap of the simulated cardiac implant 42 withthe segmented locally adjacent region 40 is calculated. In the givenexample it is calculated to what extent the anterior mitral leaflet 34projects into the virtual cardiac implant 42. This calculated overlap isschematically illustrated in FIG. 4 and indicated by reference numeral46. This is preferably done for each frame of the 3D image sequence.

The trajectories of several segmented points on the anterior mitralleaflet 34 may thereto be determined from the segmented, registeredmeshes (see segmentation step S12) with reference to the definedcoordinate system. In the next step, the collision evaluation unit 26preferably determines in each of the plurality of 3D cardiac images 14,14′ the overlap at a plurality of different spatial locations along thez-axis in order to receive the overlap information in each frame as afunction of the longitudinal axis of the target implant region 38.

Furthermore, the collision evaluation unit 26 is configured to determinefor each of the plurality of different spatial locations a maximumoverlap 46 by comparing the overlaps 46 occurring in each frame of the3D image sequence at the respective spatial locations with each other.This way, the extent of the maximum overlap at each position on thez-axis is determined. In order to facilitate the calculations, thecollision evaluation unit 26 preferably only evaluates the maximumoverlap for specific distinctive points on the z-axis (e.g. with a stepsize of 2.5 mm).

The above-mentioned collision calculation/evaluation may be performed bycombining all segmented and registered points of the anterior mitralleaflet 34 that have been found in the segmentation S12 into a pointcloud. The points of this point cloud may then be merged into groupsaccording to the defined step size. For every group of points, themaximum overlap may then be calculated to receive the maximum overlap atthe different positions on the z-axis.

5. Fifth Method Step S18 (“Feedback”)

Finally, the feedback information concerning the calculated overlap 46may be given out via the feedback unit 28. One example of such afeedback is shown in FIG. 7.

FIG. 7 shows a graphical representation 48 that illustrates the maximumoverlaps 46 as a function of the different spatial locations along thez-axis. It is to be understood that these maximum overlap values arerelative maxima, meaning the maximal overlap values that occur at thespecific positions during a cardiac cycle. Each maximum overlap isreceived by evaluating the overlap at the respective position in eachframe and comparing it to the values occurring at said position in theother frames.

The graphical representation 48 shows several overlap curves that havebeen determined from 3D TEE data sets of eighteen different patients.Each curve shows the maximum overlap between the mitral leafletmovement, and the virtual cardiac implant 42 as a function of thedistance from the aortic annulus plane. Therefore, it can be seen thatthe absolute maximum overlap (point with largest overlap in each curve)varies considerably between patients, wherein not only the extent of theabsolute maximum varies, but also the positions where the absolutemaximum occurs. The patient with the smallest overlap (indicated byreference numeral 50) has an absolute maximum overlap of around 4.7 mm,whereas the patient with the largest overlap (indicated by referencenumeral 52) has an absolute maximum overlap of around 16.6 mm. Also, therelative maximum overlap at a given implant depth varies considerably.At an implant depth of 12.5-15 mm, which is a typical depth for thelower rim of commercially available implants, the overlap varies betweenaround 2.6 and 13.4 mm.

These individual differences may be also seen from the exemplarysegmentations shown in FIGS. 8A and 8B. Both images show the heart oftwo different patients at a point in time during the cardiac cycle whenthe mitral valve is opened. By comparing the two images with each other,it can be seen that the overlap between the anterior mitral leaflet andthe left ventricular outflow tract prolongation is quite different. InFIG. 8A, the overlap has an extent of around 8 mm, while the maximumoverlap is located quite far from the aortic annulus plane. In FIG. 8B,the maximum overlap is over 15 mm and located a lot closer to the aorticannulus plane.

The given results show that the system and method according to thepresent invention is a powerful tool for planning an implantation of acardiac implant. A graphical representation as given in FIG. 7simplifies the risk evaluation a lot for the physician and also allowshim to easily select the correctly shaped and sized cardiac implants.

In summary, the presented method allows to accurately plan animplantation of a cardiac implant, either in advance to or during thesurgery. It allows to dynamically segment a series of medical 3D imagesand to calculate or estimate an overlap of the dynamical heart modelwith a virtual implant model. Even though the foregoing description hasbeen mainly focused on TAVI, the presented method may also be used forplanning other cardiac implants in other regions of the heart. It shallbe also noted that the invention is not limited to a specific type ofmedical image (MR, CT, ultrasound), but may be implemented for variousmedical imaging techniques.

While the invention has been illustrated and described in detail in thedrawings and foregoing description, such illustration and descriptionare to be considered illustrative or exemplary and not restrictive; theinvention is not limited to the disclosed embodiments. Other variationsto the disclosed embodiments can be understood and effected by thoseskilled in the art in practicing the claimed invention, from a study ofthe drawings, the disclosure, and the appended claims.

In the claims, the word “comprising” does not exclude other elements orsteps, and the indefinite article “a” or “an” does not exclude aplurality. A single element or other unit may fulfill the functions ofseveral items recited in the claims. The mere fact that certain measuresare recited in mutually different dependent claims does not indicatethat a combination of these measures cannot be used to advantage.

A computer program may be stored/distributed on a suitable medium, suchas an optical storage medium or a solid-state medium supplied togetherwith or as part of other hardware, but may also be distributed in otherforms, such as via the Internet or other wired or wirelesstelecommunication systems.

Any reference signs in the claims should not be construed as limitingthe scope.

The invention claimed is:
 1. A medical imaging system for planning an implantation of a cardiac implant, comprising: an interface configured to receive a plurality of three-dimensional (3D) cardiac images showing different conditions of a heart during a cardiac cycle; a processor in communication with the interface, wherein the processor is programmed to: receive, via the interface, the plurality of 3D cardiac images; segment within the plurality of 3D cardiac images a target implant region and a locally adjacent region that could interfere with the cardiac implant, wherein the target implant region is a part of a left ventricular outflow tract and the locally adjacent region is a part of a mitral valve; simulate the implantation of the cardiac implant within the target implant region in at least two of the plurality of 3D cardiac images; evaluate an overlap of the simulated cardiac implant with the segmented locally adjacent region in at least two of the plurality of 3D cardiac images; determine in each of the plurality of 3D cardiac images the overlap at a plurality of different spatial locations along a longitudinal axis (z) along which the target implant region substantially extends as a function of a depth of the cardiac implant; and provide feedback information, via a feedback unit, to a user indicative of the overlap evaluated.
 2. The medical imaging system according to claim 1, wherein the processor is further programmed to simulate the implantation of the cardiac implant within the target implant region in each of the plurality of 3D cardiac images; and evaluate the overlap of the simulated cardiac implant with the segmented locally adjacent region in each of the plurality of 3D cardiac images.
 3. The medical imaging system according to claim 1, wherein the processor is further programmed to provide feedback information to the user indicative of the overlap evaluated in each of the plurality of 3D cardiac images.
 4. The medical imaging system according to claim 1, wherein the processor is further programmed to provide feedback information including a quantified extent of the overlap and/or a location where the overlap occurs in the 3D cardiac images.
 5. The medical imaging system according to claim 1, wherein the processor is further programmed to determine for each of the plurality of different spatial locations a maximum overlap by comparing the overlaps in the 3D cardiac images at the respective spatial locations with each other.
 6. The medical imaging system according to claim 5, wherein the processor is further programmed to provide a graphical representation illustrating the maximum overlaps as a function of the different spatial locations along the longitudinal axis (z).
 7. The medical imaging system according to claim 5, wherein the maximum overlap is determined at a plurality of spatial locations along the longitudinal axis according to a defined step size.
 8. The medical imaging system according to claim 5, further comprising selecting one of the plurality of 3D cardiac images in which the maximum overlap is determined for each spatial location on the longitudinal axis.
 9. The medical imaging system according to claim 1, wherein the processor is further programmed to simulate the cardiac implant by means of a virtual model having an elliptical cross-section, wherein a normal to the elliptical cross-section coincides with a longitudinal axis (z) along which the target implant region substantially extends.
 10. The medical imaging system according to claim 1, wherein the processor is further programmed to allow a user to vary one or more of a size, a shape, or a position of the simulated cardiac implant.
 11. The medical imaging system according to claim 1, wherein the processor is further programmed to segment the target implant region and the locally adjacent region based on a model-based segmentation.
 12. The medical imaging system according to claim 1, wherein the interface is further configured to receive the plurality of cardiac 3D images including 3D transesophageal echocardiography images acquired with an ultrasound imaging system.
 13. The medical imaging system according to claim 1, wherein the locally adjacent region includes a mitral valve leaflet.
 14. The medical imaging system according to claim 13, wherein the processor is further configured to determine segmented trajectories for a plurality of different surface points on the mitral valve leaflet.
 15. The medical imaging system according to claim 14, wherein the overlap of the simulated cardiac implant with the segmented locally adjacent region is calculated by determining intersections between segmented trajectories of the mitral valve leaflet and the simulated cardiac implant.
 16. The medical imaging system according to claim 1, wherein the plurality of different spatial locations along the longitudinal axis (z) is referenced with respect to an aortic annulus plane.
 17. A medical imaging system for planning an implantation of a cardiac implant, comprising: an interface configured to receive a plurality of three-dimensional (3D) cardiac images showing different conditions of a heart during a cardiac cycle; a processor in communication with the interface, wherein the processor is programmed to: receive, via the interface, the plurality of 3D cardiac images; segment within the plurality of 3D cardiac images a target implant region and a locally adjacent region that could interfere with the cardiac implant, wherein the target implant region is a part of a right ventricular outflow tract and the locally adjacent region is a part of a tricuspid valve; simulate the implantation of the cardiac implant within the target implant region in at least two of the plurality of 3D cardiac images; evaluate an overlap of the simulated cardiac implant with the segmented locally adjacent region in at least two of the plurality of 3D cardiac images; determine in each of the plurality of 3D cardiac images the overlap at a plurality of different spatial locations along a longitudinal axis (z) along which the target implant region substantially extends as a function of a depth of the cardiac implant; and provide feedback information, via a feedback unit, to a user indicative of the overlap evaluated.
 18. A method for planning an implantation of a cardiac implant, comprising the steps of: receiving a plurality of three-dimensional (3D) cardiac images showing different conditions of a heart during a cardiac cycle; segmenting within the plurality of 3D cardiac images a target implant region and a locally adjacent region that could interfere with the cardiac implant, wherein the target implant region is a part of a left ventricular outflow tract and the locally adjacent region is a part of a mitral valve; simulating the implantation of the cardiac implant within the target implant region in at least two of the plurality of 3D cardiac images; evaluating an overlap of the simulated cardiac implant with the segmented locally adjacent region in at least two of the plurality of 3D cardiac images; determining for each of the plurality of 3D cardiac images a maximum overlap along a longitudinal axis (z) along which the target implant region substantially extends as a function of a depth of the cardiac implant by comparing the overlaps in the 3D cardiac images with each other; and providing feedback information to a user concerning the evaluated overlap.
 19. A method for planning an implantation of a cardiac implant, comprising the steps of: receiving a plurality of three-dimensional (3D) cardiac images showing different conditions of a heart during a cardiac cycle; segmenting within the plurality of 3D cardiac images a target implant region and a locally adjacent region that could interfere with the cardiac implant, wherein the target implant region is a part of a right ventricular outflow tract and the locally adjacent region is a part of a tricuspid valve; simulating the implantation of the cardiac implant within the target implant region in at least two of the plurality of 3D cardiac images; evaluating an overlap of the simulated cardiac implant with the segmented locally adjacent region in at least two of the plurality of 3D cardiac images; determining for each of the plurality of 3D cardiac images a maximum overlap along a longitudinal axis (z) along which the target implant region substantially extends as a function of a depth of the cardiac implant by comparing the overlaps in the 3D cardiac images with each other; and providing feedback information to a user concerning the evaluated overlap.
 20. A computer program product comprising a non-transitory computer readable medium encoded with program code, which when executed by a processor, enable the processor to: receive a plurality of three-dimensional (3D) cardiac images showing different conditions of a heart during a cardiac cycle; segment within the plurality of 3D cardiac images a target implant region and a locally adjacent region that could interfere with the cardiac implant; simulate the implantation of the cardiac implant within the target implant region in at least two of the plurality of 3D cardiac images; evaluate an overlap of the simulated cardiac implant along a longitudinal axis (z) along which the cardiac implant substantially extends into the segmented locally adjacent region as a function of a depth of the cardiac implant in at least two of the plurality of 3D cardiac images; and provide feedback information to a user concerning the evaluated overlap. 